Constrained Graphic Layout Generation via Latent Optimization
원문 초록
It is common in graphic design humans visually arrange various elements according to their design intent and semantics. For example, a title text almost always appears on top of other elements in a document. In this work, we generate graphic layouts that can flexibly incorporate such design semantics, either specified implicitly or explicitly by a user. We optimize using the latent space of an off-the-shelf layout generation model, allowing our approach to be complementary to and used with existing layout generation models. Our approach builds on a generative layout model based on a Transformer architecture, and formulates the layout generation as a constrained optimization problem where design constraints are used for element alignment, overlap avoidance, or any other user-specified relationship. We show in the experiments that our approach is capable of generating realistic layouts in both constrained and unconstrained generation tasks with a single model. The code is available at https://github.com/ktrk115/const_layout .
함께 살펴볼 논문
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FoREST: Frame of Reference Evaluation in Spatial Reasoning Tasks
Smaller But Better: Unifying Layout Generation with Smaller Large Language Models
DogLayout: Denoising Diffusion GAN for Discrete and Continuous Layout Generation
HiCo: Hierarchical Controllable Diffusion Model for Layout-to-image Generation
토론
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